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9th International conference on Cloud Computing and internet of Things, CCIOT 2024

ISBN: (纸本)9798400717161

The proceedings contain 18 papers. The topics discussed include: research on RedCap UE’s performance indicators in real network to support IoT applications;machine learning-based crop recommendation for IoT-enabled smart agriculture;cloud provisioning: a highly optimized, cost-effective, and efficient deployment model;smart pill box: an IoT-integrated application for monitoring patient medication usage at home;analyzing cybersecurity risk with a phishing simulation website;agile infrastructure: adapting systems to changing business requirements;a secure and efficient privacy scheme for location-based services in cloud environments;and research on garbled circuits-based identity authentication and ciphertext hidden access control in vehicular networks.

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FedLoRa: IoT Spectrum Sensing Through Fast and Energy-Efficient Federated Learning in LoRa networks 21

FedLoRa: IoT Spectrum Sensing Through Fast and Energy-Effici...

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21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Busacca, Fabio Mangione, Stefano Neglia, Giovanni Tinnirello, Ilenia Palazzo, Sergio Restuccia, Francesco Univ Catania Dept Elect Elect & Comp Engn DIEEI Catania Italy Univ Palermo Dept Engn Palermo Italy Univ Cote dAzur INRIA Nice France Northeastern Univ Inst Wireless Internet Things Boston MA 02115 USA

ISBN: (纸本)9798350363999;9798350364002

Effective spectrum sensing is quintessential to decrease spectrum congestion across time, space and frequency in internet of Things (IoT) networks. To circumvent the severe bandwidth constraints of IoT networks, federated machine learning (FML) can be used, but it is still unclear whether FML can be successfully performed in resource-constrained bandwidth-limited IoT networks. In this paper, we demonstrate for the first time that FML can tolerate losses up to a certain percentage and still converge. Then, we leverage this key result to design FedLoRa, an optimization networks for LoRa that is (i) fast, as it reduces the FML round time in comparison with other resource allocation schemes;(ii) energy-efficient, as the time reduction does not imply a higher energy consumption. The key idea is to balance the network load over the available spreading factors, and to exploit sequential polling of nodes to maximize the number of simultaneous non-interfering transmissions, leading to a shorter FML round time. As the problem is NP-Hard, we provide an approximation algorithm. We evaluate the performance of FedLoRa through experimental evaluation on the Colosseum channel emulator, as well as with real-world data collection with off-the-shelf LoRa devices in an 5kmx5km urban setting in Portland, Maine. Our results show that FedLoRa reduces the round time by up to about 35%, as compared to the baselines.

关键词： internet of Things LoRa Machine Learning Resource Allocation Spectrum Sensing

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Robust Intrusion Detection for Resilience Enhancement of Industrial control systems: An Extended State Observer Approach

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2023年第6期59卷 7735-7743页

作者： Ahmad, Saif Ahmed, Hafiz INP ENSEEIHT Lab Plasma & Convers Energie F-31071 Toulouse France Univ Sheffield Nucl AMRC Midlands Derby DE73 5SS England

We address the problem of attack signal estimation in industrial control systems that are subjected to actuator false data injection attack (FDIA) and where the sensor measurements are corrupted by non-negligible high-frequency measurement noise. The actuator FDIA signal is categorized as disturbance to be estimated and subsequently compensated, based on the concept of extended state observer (ESO). We investigate the efficacy of two alternatives to conventional ESO namely, cascade ESO (CESO) and low-power higher-order ESO (LHESO), that guarantee improved estimation performance in case of noisy measurement data as well as time-varying attack signals. Simulation and experimental results under different types of FDIAs demonstrate the advantages of designed schemes in comparison to conventional linear and nonlinear ESOs, using network motion control system as an illustrative example. The results highlight the limitations of conventional ESO under noisy measurement data, particularly nonlinear ESO which is based on fal(center dot) function and commonly used in control literature.

关键词： Actuator false data injection attack extended state observer industrial control system measurement noise

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REINFORCEMENT LEARNING-BASED SECURE VIDEO TRANSMISSION FOR IOV systems 31

REINFORCEMENT LEARNING-BASED SECURE VIDEO TRANSMISSION FOR I...

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2024 International conference on Image Processing

作者： Liu, Lixin Liu, Zhibo Lu, Luxiaozhen Bu, Yanling Han, Bin Xiao, Liang Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Communicat & Informat Engn Nanjing Peoples R China Xiamen Univ Dept Informat & Commun Engn Xiamen Peoples R China

ISBN: (纸本)9798350349405;9798350349399

The rapid growth in the number of vehicles and types of services such as video transmission improves the quality-of-service (QoS) requirements and increases the difficulty in resisting eavesdropping attacks on the internet of Vehicles (IoV). Existing video transmission schemes that either ignore the impact of eavesdropping attacks or have the full knowledge of the attack model have performance degradation in highly dynamic IoV systems. In this paper, we propose a reinforcement learning-based secure video transmission scheme for IoV systems, which jointly optimizes the access control policy for each vehicle (i.e., the selection of access nodes such as the base stations or unmanned aerial vehicles) and the corresponding transmit power level against active eavesdropping. This scheme uses the QoS and eavesdropping rate as the criteria to evaluate the long-term risk of each state-action pair, which is estimated by a designed deep Q-network to avoid the risky access control policies that cause severe data leakage or video transmission failure. Simulation results show that our scheme reduces the energy consumption, transmission latency, and eavesdropping rate compared with the benchmark.

关键词： internet of Vehicles video transmission eavesdropping reinforcement learning

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Enhancing IoT network Intrusion Detection with a New GraphSAGE Embedding Algorithm Using Centrality Measures 10

Enhancing IoT Network Intrusion Detection with a New GraphSA...

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10th International conference on internet of Things, Big Data and Security, IoTBDS 2025

作者： Termos, Mortada Ghalmane, Zakariya Brahmia, Mohamed-El-Amine Fadlallah, Ahmad Jaber, Ali Zghal, Mourad CESI LINEACT UR 7527 Strasbourg France Computer Science Department Faculty of Sciences Lebanese University Beirut Lebanon Beirut Lebanon

ISBN: (纸本)9789897587504

The rapid expansion of the internet of Things (IoT) has led to many opportunities in addition to introducing complex security challenges, necessitating more powerful network Intrusion Detection systems (NIDS). This study addresses this challenge by enhancing Graph Neural networks (GNNs) with centrality measures to improve intrusion detection performance in IoT environments. We propose the so-called"Centrality-based E-GraphSAGE", an extension to the E-GraphSAGE model incorporating the centrality measures: Degree, Betweenness, Closeness, PageRank, and K-truss. These centrality measures, which highlight both the local and global influence of nodes (IoT devices), can uncover hidden patterns and relationships in network traffic data, thereby enhancing the performance of IDS systems. The centrality-informed initialization of node embeddings aids the model in capturing critical structural insights in the graph. The inclusion of residual connections further improves classification accuracy. Our models were evaluated on four datasets: NF-UQ-NIDS, NF-CSE-CIC-IDS2018, CCD-INID, and X-iioTID. Results showed significant performance gains in accuracy of detection evaluated using F1-score and reduced number of false alarms. This work paves the way for more advanced and robust intrusion detection systems to improve the security of IoT networks. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Graph neural networks

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Research on Auxiliary Terminal System of Power Communication Operation and Maintenance Based on Augmented Reality Technology 6

Research on Auxiliary Terminal System of Power Communication...

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6th IEEE International conference on Power, Intelligent Computing and systems, ICPICS 2024

作者： Hao, Xue Geng, Lizhuo Liu, Lu Wang, Xunshi Lin, Chunlong Fan, Yunkun State Grid Hebei Electric Power Company Limited Training Center Shijiazhuang China Beijing Kedong Electric Power Control System Company Limited Simulation Branch Beijing China

ISBN: (纸本)9798350374315

An intelligent operation and maintenance system of power communication network based on the internet of Things is established. The mobile operation management system of the internet of Things is used to accurately collect, process and configure the mobile communication data of electric energy. The power intelligent communication operation management system and the internet of Things data configuration processing platform are organically combined to achieve the improvement and optimization of the power communication mobile intelligent system. A new algorithm using Bayesian algorithm to detect suspicious faults in power networks;Then, using the data obtained from the integrated RRPMS, the alarm of the communication network management system, and the scheduling integrated operation management OBS, the effective control of the accident is realized. The test shows that the mobile phone network operation and maintenance system designed in this project can meet the actual demand, and its working reliability is greater than 80%. Compared with the conventional method, its performance is improved by 20% to 30% to achieve the purpose of standardization and intelligence. The system improves grid operational efficiency. © 2024 IEEE.

关键词： Information management

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Enabling Communications for Industry 4.0: Private 5G in Smart Manufacturing 34

Enabling Communications for Industry 4.0: Private 5G in Smar...

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34th Irish Signals and systems conference (ISSC)

作者： O'Brien, William Hayes, Martin Penica, Mihai McCann, Jeff Moore, Denis O'Connell, Eoin Univ Limerick Dept Elect & Comp Engn Limerick Ireland

ISBN: (纸本)9798350340570

High performance networking is at the core of every industrial system, as more and more companies look inwards towards the digital transformation of their entire manufacturing environment. The driving factor for all these changes is Industry 4.0, there are many options for communication systems for the latest generations of hardware with one of the most promising technologies being private 5G networks. A smart automation use case will be implemented using private 5G as the communication backbone, the performance of this communication type will be compared to other communication types that were historically used within smart automation and manufacturing settings. performance metrics will be compared to show typical performance that may be expected when deploying a private 5G communication network. The paper will also explore the roadmap for future 5G performance increases through updates and network optimization.

关键词： 5G Private 5G Smart Manufacturing Automation Industry 4.0 Robotic control Spectrum internet of Things

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Investigation on End-To-End Congestion control Algorithm in Multi-Hop Ad-Hoc network 9

Investigation on End-To-End Congestion Control Algorithm in ...

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9th International conference on Wireless Communications, Signal Processing and networking, WiSPNET 2024

作者： Joseph Auxilius Jude, M. Diniesh, V.C. Sneha, A. Subhika, S. Vimal Sanjeevi, S. Sri Yaalini, M. ECE Kongu Engineering College Perundurai India

ISBN: (纸本)9798350350845

A multi-hop wireless network forms a formidable solution to overcome spectrum deficit and coverage issues in wireless conditions. As wireless internet remains crucial in connecting people from remote locations, a vast chunk of web traffic relies solely on Transmission control Protocol (TCP) to deliver packets between end systems. In the paper, an initiative is made to analyze the traffic stability under a multi-hop wireless link. TCP manages congestion by adjusting the transmission window size. In this regard, two diverse end-To-end traffic or congestion control algorithms, i.e., linear and concave-based window growth patterns, are subjected to evolution in mobility, traffic, and error rate conditions. The traffic performance of the wireless network is measured with these algorithms using network Simulator-3 (NS-3). © 2024 IEEE.

关键词： Transmission control protocol

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Securing Industrial systems: A Testbed for Cyber-Defense Evaluation and Data Collection 20

Securing Industrial Systems: A Testbed for Cyber-Defense Eva...

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20th International conference on network and Service Management

作者： Cuorvo, Raffaele d'Ambrosio, Nicola Iorio, Domenico Perrone, Gaetano Romano, Simon Pietro Univ Naples Federico II Dept Elect Engn & Informat Technol Naples Italy

ISBN: (纸本)9798331505158;9783903176669

Over recent years, many Industrial control System (ICS) components have been exposed to both the internet and corporate networks to enhance the management of industrial processes. However., this increased exposure has often taken place without adequate consideration for cybersecurity, making industrial networks more vulnerable to cyberattacks. In this context, digital twins have emerged as innovative solutions to evaluate novel cyber-defense strategies that can mitigate threats affecting industrial networks. Unfortunately, to the best of the authors' knowledge, there is no digital twin that is flexible enough to integrate both physical and virtualized components according to user preferences while simultaneously supporting novel approaches based on the Software-Defined networking (SDN) paradigm. To address these issues, we developed a flexible hybrid/virtual digital twin that mimics a physical Microgrid testbed known as EPIC. Specifically, our solution leverages virtualization and containerization to create a lightweight platform that can include the widest possible range of vulnerabilities. Furthermore, we employ Open vSwitch to implement SDN-based methodologies and integrate physical components into our platform. Lastly, we provide a comprehensive tool that collects all possible logs from the testbed.

关键词： Industrial control System Smartgrid Testbed Software Defined network Digital Twin

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Research on PID control method for predictive modeling of oil pipeline infrastructure under industrial internet of things driving

Research on PID control method for predictive modeling of oi...

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2024 International conference on Algorithms, High performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Liu, Hao Dong, Hongbing Wang, Bo Xu, Yang Cai, Zhongwei Li, Xiang China Kunming China Oil & Gas Pipeline Network Corporation Yunnan Branch 650500 China

ISBN: (纸本)9781510685840

The oil pipeline system faces numerous safety hazards and operational management challenges, such as leaks, blockages, and pressure fluctuations, which may lead to environmental pollution, economic losses, and even casualties. To address these issues, this study proposes a predictive PID control method for oil pipeline infrastructure based on cloud servers and Industrial internet of Things (iioT) technology, coupled with advanced data analysis and control algorithms, enabling comprehensive monitoring and management of oil pipeline systems. A risk assessment and control framework based on online model fusion is developed, integrating diverse data sources and optimization model algorithms to achieve intelligent monitoring and control of pipeline systems. Additionally, PID control algorithms are employed for real-time adjustment of flow rates and pressures in the pipeline system to ensure stable operation. Experimental results demonstrate that the proposed risk assessment and control framework effectively identifies anomalies in the pipeline system, while the PID control algorithm enables real-time adjustment of flow rates and pressures, enhancing the safety and stability of the pipeline system. Comparative analysis shows that the proposed control method offers a 28.96% improvement in feedback control effectiveness and can reduce the risk rate by up to 4.2 times through the predictive modeling method. © 2024 SPIE.

关键词： Feedback control

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